Similarity corpus on microbial transcriptional regulation
Abstract Background The ability to express the same meaning in different ways is a well-known property of natural language. This amazing property is the source of major difficulties in natural language processing. Given the constant increase in published literature, its curation and information extr...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-05-01
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| Series: | Journal of Biomedical Semantics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13326-019-0200-x |
| _version_ | 1818521723103870976 |
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| author | Oscar Lithgow-Serrano Socorro Gama-Castro Cecilia Ishida-Gutiérrez Citlalli Mejía-Almonte Víctor H. Tierrafría Sara Martínez-Luna Alberto Santos-Zavaleta David Velázquez-Ramírez Julio Collado-Vides |
| author_facet | Oscar Lithgow-Serrano Socorro Gama-Castro Cecilia Ishida-Gutiérrez Citlalli Mejía-Almonte Víctor H. Tierrafría Sara Martínez-Luna Alberto Santos-Zavaleta David Velázquez-Ramírez Julio Collado-Vides |
| author_sort | Oscar Lithgow-Serrano |
| collection | DOAJ |
| description | Abstract Background The ability to express the same meaning in different ways is a well-known property of natural language. This amazing property is the source of major difficulties in natural language processing. Given the constant increase in published literature, its curation and information extraction would strongly benefit from efficient automatic processes, for which corpora of sentences evaluated by experts are a valuable resource. Results Given our interest in applying such approaches to the benefit of curation of the biomedical literature, specifically that about gene regulation in microbial organisms, we decided to build a corpus with graded textual similarity evaluated by curators and that was designed specifically oriented to our purposes. Based on the predefined statistical power of future analyses, we defined features of the design, including sampling, selection criteria, balance, and size, among others. A non-fully crossed study design was applied. Each pair of sentences was evaluated by 3 annotators from a total of 7; the scale used in the semantic similarity assessment task within the Semantic Evaluation workshop (SEMEVAL) was adapted to our goals in four successive iterative sessions with clear improvements in the agreed guidelines and interrater reliability results. Alternatives for such a corpus evaluation have been widely discussed. Conclusions To the best of our knowledge, this is the first similarity corpus—a dataset of pairs of sentences for which human experts rate the semantic similarity of each pair—in this domain of knowledge. We have initiated its incorporation in our research towards high-throughput curation strategies based on natural language processing. |
| first_indexed | 2024-12-11T01:55:12Z |
| format | Article |
| id | doaj.art-f133b23bf096497ca7efcbaa05005aec |
| institution | Directory Open Access Journal |
| issn | 2041-1480 |
| language | English |
| last_indexed | 2024-12-11T01:55:12Z |
| publishDate | 2019-05-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Biomedical Semantics |
| spelling | doaj.art-f133b23bf096497ca7efcbaa05005aec2022-12-22T01:24:38ZengBMCJournal of Biomedical Semantics2041-14802019-05-0110111410.1186/s13326-019-0200-xSimilarity corpus on microbial transcriptional regulationOscar Lithgow-Serrano0Socorro Gama-Castro1Cecilia Ishida-Gutiérrez2Citlalli Mejía-Almonte3Víctor H. Tierrafría4Sara Martínez-Luna5Alberto Santos-Zavaleta6David Velázquez-Ramírez7Julio Collado-Vides8Computational Genomics, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México (UNAM). A.P.Computational Genomics, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México (UNAM). A.P.Computational Genomics, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México (UNAM). A.P.Computational Genomics, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México (UNAM). A.P.Computational Genomics, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México (UNAM). A.P.Computational Genomics, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México (UNAM). A.P.Computational Genomics, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México (UNAM). A.P.Computational Genomics, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México (UNAM). A.P.Computational Genomics, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México (UNAM). A.P.Abstract Background The ability to express the same meaning in different ways is a well-known property of natural language. This amazing property is the source of major difficulties in natural language processing. Given the constant increase in published literature, its curation and information extraction would strongly benefit from efficient automatic processes, for which corpora of sentences evaluated by experts are a valuable resource. Results Given our interest in applying such approaches to the benefit of curation of the biomedical literature, specifically that about gene regulation in microbial organisms, we decided to build a corpus with graded textual similarity evaluated by curators and that was designed specifically oriented to our purposes. Based on the predefined statistical power of future analyses, we defined features of the design, including sampling, selection criteria, balance, and size, among others. A non-fully crossed study design was applied. Each pair of sentences was evaluated by 3 annotators from a total of 7; the scale used in the semantic similarity assessment task within the Semantic Evaluation workshop (SEMEVAL) was adapted to our goals in four successive iterative sessions with clear improvements in the agreed guidelines and interrater reliability results. Alternatives for such a corpus evaluation have been widely discussed. Conclusions To the best of our knowledge, this is the first similarity corpus—a dataset of pairs of sentences for which human experts rate the semantic similarity of each pair—in this domain of knowledge. We have initiated its incorporation in our research towards high-throughput curation strategies based on natural language processing.http://link.springer.com/article/10.1186/s13326-019-0200-xCorpusSimilarityTranscriptional-regulationGenomics |
| spellingShingle | Oscar Lithgow-Serrano Socorro Gama-Castro Cecilia Ishida-Gutiérrez Citlalli Mejía-Almonte Víctor H. Tierrafría Sara Martínez-Luna Alberto Santos-Zavaleta David Velázquez-Ramírez Julio Collado-Vides Similarity corpus on microbial transcriptional regulation Journal of Biomedical Semantics Corpus Similarity Transcriptional-regulation Genomics |
| title | Similarity corpus on microbial transcriptional regulation |
| title_full | Similarity corpus on microbial transcriptional regulation |
| title_fullStr | Similarity corpus on microbial transcriptional regulation |
| title_full_unstemmed | Similarity corpus on microbial transcriptional regulation |
| title_short | Similarity corpus on microbial transcriptional regulation |
| title_sort | similarity corpus on microbial transcriptional regulation |
| topic | Corpus Similarity Transcriptional-regulation Genomics |
| url | http://link.springer.com/article/10.1186/s13326-019-0200-x |
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